Abstract: This paper investigates the impact of loop unrolling on CUDA matrix multiplication operations’ performance across NVIDIA GPUs. We benchmarked both basic and unrolled kernels with varying ...

Abstract: The demand for efficient, low-power, and high-speed deep neural network (DNN) accelerators has driven the need for specialized hardware architectures. This work presents the VLSI ...

The inner loop (j) completes all its iterations for each iteration of the outer loop (i). This is how the multiplication table is generated row by row. The formatting {product:4} ensures consistent ...

While we have the Python built-in function sum() which sums the elements of a sequence (provided the elements of the sequence are all of numeric type), it’s instructive to see how we can do this in a ...

Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiński.

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This is an archived article and the information in the article may be outdated. Please look at the time stamp on the story to see when it was last updated. CHICAGO — A proposal to create a quiet zone ...

Do you want to better track team projects? With Loop, you can make rules that use Microsoft Power Automate to run tasks that take a lot of time and effort—so you can focus on more important and ...

Microsoft Loop introduces a new board visualization for Loop tables after the previous board templates for Loop were well received by users. We’ve heard from many of you that you enjoy and value our ...

The Hechinger Report covers one topic: education. Sign up for our newsletters to have stories delivered to your inbox. Consider becoming a member to support our nonprofit journalism. A study published ...